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A Novel Neural Network Based on Immunity

机译:一种基于免疫的新型神经网络

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摘要

Based on analyzing natural immune phenomena and utilizing performances of the existing artificial neural networks, a novel network model (artificial neural network based on immunity-ANNI) is proposed which integrates the immune mechanism and the function of neural information processing. The learning algorithm of ANNI contains the method of selecting an excitation function and an adaptive algorithm of network learning. ANNI makes it easy for a user to use the characteristic information of a pending problem and to simplify the original network structure, and therefore is able to make the efficiency and the accuracy improved obviously. Besides theoretic analysis, simulation on the twin-spiral problem also shows that ANNI is not only effective but also feasible.
机译:在分析自然免疫现象的基础上,利用现有人工神经网络的性能,提出了一种结合免疫机制和神经信息处理功能的新型网络模型(基于免疫-ANNI的人工神经网络)。 ANNI的学习算法包括选择激励函数的方法和网络学习的自适应算法。 ANNI使用户易于使用待解决问题的特征信息并简化原始网络结构,因此能够使效率和准确性明显提高。除了理论分析,对双螺旋问题的仿真还表明,ANNI不仅有效而且可行。

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